Tableau connect to aws postgresql database
Imagine you only had start and end dates for an event, but wanted to distribute a measure across those dates. The ‘scaffolding’ technique can also help create a continuous date field or axis if your original data source doesn’t have one. I unfortunately found this out the hard way, but hopefully you won’t with this guidance. You must create all joins first, and then go back and union within your established data sources. If you union tables within your data sources and then join like I did, you’ll also need to follow a very specific order or Tableau will throw an error.
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The ‘Organize by Folder’ option is a great way to store fields in an orderly manner. I also like to create naming conventions and acronyms for my fields to easily swap them in and out of calculations. Keep in mind that your data sets have a lot of columns, then you must create a lot of calculated fields, potentially impacting performance. Additional Considerations and TipsĬross-database unions aren’t pretty, but they get the job done. There we go! We have successfully unioned data from two different databases. I split the data set into two files, one with data from East and West regions and the other with data from Central and South. To explain how this works in detail, I will use Sample Superstore data. Tutorial: Step by Step Cross-Database Union in Tableau We only had to consolidate measures for this project.
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We were also used the BU and Date fields from the forecast data source without consolidating since they existed on every row. I only included one metric for simplicity. Luckily, this was a high-level dashboard, so we structured the custom SQL queries to give us only three rows of data per day (one per BU), so performance was not a factor.īelow is a simplified example of what one day of records looks like in the final data source. We ended up with 193 columns total after creating all calculations.
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Each data source had between five and ten original columns, depending on what metrics were involved, for a total of 48 columns. This consolidation process proved extra tricky because we needed to weight measures on a daily level and also perform ratio calculations between them. The next step was creating consolidated fields for the dashboard, because the cross join produces null values in a third of the cells. This cross join gave us all needed rows in one data source. Digital Analytics Platform Implementation.